Language at the Heart of Lobbying Dynamics - A Quantitative Approach to Interest Group Research

Sammanfattning

Within the issue area of lobbying dynamics in the European Union, the measurement of interest group success is heavily debated among scholars. This research examines the influence interest groups had in shaping the Artificial Intelligence Act via the Public Consultation process. In contrast to existing literature, a computer assisted quantitative content analysis was used to gain insights into lobbying processes, thus avoiding influencing the outcome of the study through interviews with the investigated political actors. The research design puts specific emphasize on the direct exchange of information as the key resource that influences success, thus analyzing the exercise of power rather than the bases of power. The findings thus have twofold implications for the grander lobbying literature. Next to the common empirical findings the aim of this paper is to elaborate upon the methodological challenges of interest group research and why policy position and therefore success of interest groups ought to be analyzed via a quantitative content analysis rather than interviews of lobbyists or public officials. From an empirical standpoint, the findings suggest that the smaller coalition of civil society interest groups achieved greater levels of success than anticipated, but more importantly, the applied method showed that analysis of interest groups can happen via usage of algorithms, thus avoiding bias.